{"id":"W4368368735","doi":"10.1002/cjce.24940","title":"Multi‐stage fusion regression network for quality prediction of batch process","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Gansu Education Department; National Natural Science Foundation of China","keywords":"Process (computing); Computer science; Quality (philosophy); Cluster analysis; Autoencoder; Regression; Batch processing; Data mining; Artificial neural network; Artificial intelligence; Stage (stratigraphy); Regression analysis; Machine learning; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005378162,0.00009603761,0.0002010537,0.00009677326,0.00004871617,0.00001725893,0.00015407,0.00009104673,0.000007245193],"category_scores_gemma":[0.0001795493,0.00007191708,0.00009876607,0.0002818845,0.00001705052,0.00006283796,0.000004160355,0.0002096708,0.000001281156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001040867,"about_ca_system_score_gemma":0.00006843912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001823099,"about_ca_topic_score_gemma":0.0001448423,"domain_scores_codex":[0.9991661,0.0000116681,0.0003939843,0.00005598921,0.0001408744,0.0002313342],"domain_scores_gemma":[0.9994358,0.00009168027,0.00008638159,0.0001018469,0.00009605849,0.0001882122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001848733,0.000002059894,0.0001917574,0.0002608424,0.00004463911,0.000002991352,0.0003446636,0.749303,0.2480098,0.0000338312,0.0009678717,0.0008200471],"study_design_scores_gemma":[0.0006093923,0.00002355552,0.000766458,0.0002992659,0.00001800754,0.00001693343,0.00007567173,0.9451535,0.0499299,0.00003384484,0.002971623,0.0001018964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915385,0.0003351448,0.006473346,0.0001226718,0.001178073,0.0001817984,0.00003870423,0.00009431861,0.00003742198],"genre_scores_gemma":[0.9993449,0.00000431919,0.0001973689,0.000006576285,0.0003643608,0.0000101594,0.000004444703,0.00002390676,0.00004397363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1980799,"threshold_uncertainty_score":0.2932693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221314990042814,"score_gpt":0.2516430697411932,"score_spread":0.2294299198407651,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}